Seamless Navigation, 3D Reconstruction, Thermographic and Semantic Mapping for Building Inspection

We present a workflow for seamless real-time navigation and 3D thermal mapping in combined indoor and outdoor environments in a global reference frame. The automated workflow and partly real-time capabilities are of special interest for inspection tasks and also for other time-critical applications. We use a hand-held integrated positioning system (IPS), which is a real-time capable visual-aided inertial navigation technology, and augment it with an additional passive thermal infrared camera and global referencing capabilities. The global reference is realized through surveyed optical markers (AprilTags). Due to the sensor data’s fusion of the stereo camera and the thermal images, the resulting georeferenced 3D point cloud is enriched with thermal intensity values. A challenging calibration approach is used to geometrically calibrate and pixel-co-register the trifocal camera system. By fusing the terrestrial dataset with additional geographic information from an unmanned aerial vehicle, we gain a complete building hull point cloud and automatically reconstruct a semantic 3D model. A single-family house with surroundings in the village of Morschenich near the city of Jülich (German federal state North Rhine-Westphalia) was used as a test site to demonstrate our workflow. The presented work is a step towards automated building information modeling

Building Tomograph – From Remote Sensing Data of Existing Buildings to Building Energy Simulation Input

Existing buildings often have low energy efficiency standards. For the preparation of retrofits, reliable high-quality data about the status quo is required. However, state-of-the-art analysis methods mainly rely on on-site inspections by experts and hence tend to be cost-intensive. In addition, some of the necessary devices need to be installed inside the buildings. As a consequence, owners hesitate to obtain sufficient information about potential refurbishment measures for their houses and underestimate possible savings. Remote sensing measurement technologies have the potential to provide an easy-to-use and automatable way to energetically analyze existing buildings objectively. To prepare an energetic simulation of the status quo and of possible retrofit scenarios, remote sensing data from different data sources have to be merged and combined with additional knowledge about the building. This contribution presents the current state of a project on the development of new and the optimization of conventional data acquisition methods for the energetic analysis of existing buildings solely based on contactless measurements, general information about the building, and data that residents can obtain with little effort. For the example of a single-family house in Morschenich, Germany, geometrical, semantical, and physical information are derived from photogrammetry and quantitative infrared measurements. Both are performed with the help of unmanned aerial vehicles (UAVs) and are compared to conventional methods for energy efficiency analysis regarding accuracy of and necessary effort for input data for building energy simulation. The concept of an object-oriented building model for measurement data processing is presented. Furthermore, an outlook is given on the project involving advanced remote sensing techniques such as ultrasound and microwave radar application for the measurement of additional energetic building parameters

Extraktion von senkrechten Fassadenebenen aus 3D-Punktwolken von Schrägluftbildern

In dieser Arbeit wird eine Methode zur automatischen Extraktion von Fassadenebenen von Gebäuden aus einer hochaufgelösten 3D-Punktwolke von Schrägluftbildern vorgestellt. Dabei werden Methoden der lokalen Regression in der 2D-Ebene verwendet. Aus der lokalen Regression werden die lokale Richtung der Punktwolke sowie ein Maß für die Linearität der lokalen Punktwolke bestimmt. Anhand dieser Daten wird die 3D-Punktwolke nach Fassadenzugehörigkeit zu segmentiert. Weitere Algorithmen erzeugen aus der segmentierten Punktwolke den Gebäudegrundriss als geschlossenen Polygonzug. Die verwendeten Algorithmen wurden in MatLab implementiert und für Gebäude mit unterschiedlicher Komplexität angewendet

Automatisierte 3D Rekonstruktion von Gebäudeszenen aus 3D Punktwolken

Luftbildkamerasysteme mit Nadir blickenden Kameras werden zunehmend zu Oblique-Kamerasystemen erweitert. Diese Systeme erlauben es, eine 3D-Punktwolke der beobachteten Szene zu generieren anstelle der üblichen 2.5D-Informationen. Zusätzlich bedarf es robuster und automatisierter Methoden zur Rekonstruktion von Gebäuden und Gebäudeszenen, im Idealfall ganzer Dörfer und Städte. Mit der vorgestellten Methode werden größere Szenen von Gebäuden automatisiert aus Luftbilddaten rekonstruiert. Es wird gezeigt, wie zunächst die Grundrisse bestimmt werden und anschließend durch Analyse der Punktwolke ein topologisches und geometrisches Modell der Szene erstellt wird, wobei jedes Objekt mit Dachelementen und Fassaden rekonstruiert wird (LOD 2). Ohne Hinzunahme von Daten der Automatisierten Liegenschaftskarte (ALK) werden somit größere Szenen (mehr als 50 Gebäude) automatisiert abgeleitet und bezüglich Vollständigkeit und Korrektheit beurteilt

Reconstructing Buildings with Discontinuities and Roof Overhangs from Oblique Aerial Imagery

This paper proposes a two-stage method for the reconstruction of city buildings with discontinuities and roof overhangs from oriented nadir and oblique aerial images. To model the structures the input data is transformed into a dense point cloud, segmented and filtered with a modified marching cubes algorithm to reduce the positional noise. Assuming a monolithic building the remaining vertices are initially projected onto a 2D grid and passed to RANSAC-based regression and topology analysis to geometrically determine finite wall, ground and roof planes. If this should fail due to the presence of discontinuities the regression will be repeated on a 3D level by traversing voxels within the regularly subdivided bounding box of the building point set. For each cube a planar piece of the current surface is approximated and expanded. The resulting segments get mutually intersected yielding both topological and geometrical nodes and edges. These entities will be eliminated if their distance-based affiliation to the defining point sets is violated leaving a consistent building hull including its structural breaks. To add the roof overhangs the computed polygonal meshes are projected onto the digital surface model derived from the point cloud. Their shapes are offset equally along the edge normals with subpixel accuracy by detecting the zero-crossings of the second-order directional derivative in the gradient direction of the height bitmap and translated back into world space to become a component of the building. As soon as the reconstructed objects are finished the aerial images are further used to generate a compact texture atlas for visualization purposes. An optimized atlas bitmap is generated that allows perspectivecorrect multi-source texture mapping without prior rectification involving a partially parallel placement algorithm. Moreover, the texture atlases undergo object-based image analysis (OBIA) to detect window areas which get reintegrated into the building models. To evaluate the performance of the proposed method a proof-of-concept test on sample structures obtained from real-world data of Heligoland/Germany has been conducted. It revealed good reconstruction accuracy in comparison to the cadastral map, a speed-up in texture atlas optimization and visually attractive render results

True 3D Building Reconstruction – Façade, Roof and Overhang Modeling from Oblique and Vertical Aerial Imagery

Aerial imaging systems increasingly gain oblique viewing capabilities. Through these passive systems, photogrammetric 3D point clouds of a scene become available in addition to traditional vertical 2.5D information. In the field of urban reconstruction, this complementary information seeks for robust and automated fusion methods in order to derive 3D building geometry as well as topology in larger scales. It is sequentially shown how to get from façade planes over building footprints to roof reconstruction including overhangs. Façade planes are extracted from a photogrammetric high-resolution 3D point cloud. Local regression methods in 2D space are used to determine the local direction and a criterion for the local linearity of the point cloud. Based on these two parameters, the 3D point cloud is segmented according to which façade it belongs to. From the segmented point cloud, building footprints are extracted as polygons. Similar to cadaster information, those polygons, along with a traditional digital surface model (DSM), serve for one thing as the basis for overhang determination which is performed by fitting polynoms on the outside of façades and using their inflection points as overhang boundary. For another thing, they serve as roof areas which are segmented, topologically described and geometrically modelled. Again local regression methods are used but this time in 3D space in order to segment roof parts. Subsequently, the roof topology is derived using region growing methods. The final building models hold both, geometrical and topological properties

Extracting Semantically Annotated 3D Building Models with Textures from Oblique Aerial Imagery

This paper proposes a method for the reconstruction of city buildings with automatically derived textures that can be directly used for facade element classification. Oblique and nadir aerial imagery recorded by a multi-head camera system is transformed into dense 3D point clouds and evaluated statistically in order to extract the hull of the structures. For the resulting wall, roof and ground surfaces high-resolution polygonal texture patches are calculated and compactly arranged in a texture atlas without resampling. The facade textures subsequently get analyzed by a commercial software package to detect possible windows whose contours are projected into the original oriented source images and sparsely ray-casted to obtain their 3D world coordinates. With the windows being reintegrated into the previously extracted hull the final building models are stored as semantically annotated CityGML ”LOD-2.5” objects

Law requirements for GMO analysis and the role of GMO reference laboratories in Poland

Genetically modified organisms are commonly used for scientific and practical purposes. Genetically modified crops have been cultivated worldwide including EU (102 mln ha total in 2006). The use of GMO is regulated by the Directive 90/219 on contained use, Directive 2001/2003 on deliberate release to the environment, Regulation 1829/2003 on genetically modified food and feed, Regulation 1830/2003 on traceability and labeling, and the Polish GMO Law act from 2001. The regulation on food and feed implements a threshold of 0.9% GMO for product labeling. This threshold, however, can be applied to unintended or technically unavoidable GMO presence and corresponds to single ingredient only. Genetically modified organisms can be detected using DNA (PCR) or protein (ELISA) based methods. PCR screening for commonly used DNA fragments (35S promoter or Nos terminator) can be broadly applied, however the proper interpretation of the results requires good knowledge of different GMO constitution. Event specific is the most accurate PCR method for GMO identification. Quantification of GMO in products is done using a RealTime PCR. All analytical methods developed for GMO identification and quantification have to be validated before GMO approval. Validation is performed by the Community Reference Laboratory (CRL) in collaboration with National Reference Laboratories. According to Polish GMO Law the Minister of Environment is responsible for GMO control in Poland that is performed by national competent authorities (eg. Sanitary Inspection, Veterinary Inspection, Seed Inspection)

Fusion von 3D-Indoor- und Outdoor-Daten am Beispiel des Luftbildkamerasystems MACS und des Innenraum-Positionierungssystems IPS.

In dem vorliegenden Beitrag wird die Fusion von Indoor- und Outdoor-Punktwolken am Beispiel des luftgestützten Kamerasystems MACS und des Innenraum-Positionierungssystems IPS dargestellt. Dazu wurden für das Bürogebäude des Deutschen Zentrums für Luft- und Raumfahrt (DLR) in Berlin-Adlershof sowohl die Außenhülle als auch die Innenräume optisch erfasst. Mit Hilfe eines kombinierten Passpunktfeldes wurden die resultierenden diskreten Raumpunkte in ein gemeinsames Koordinatensystem überführt. Die geometrische Genauigkeit des erstellten 3D-Models wurde anhand von punktuellen Messungen mit einem Laserentfernungsmessgerät validiert

3D Visual Reconstruction as Prior Information for First Responder Localization and Visualization

In professional use cases like police or fire brigade missions, coordinated and systematic force management is crucial for achieving operational success during intervention by the emergency personnel. A real-time situation picture enhances the coordination of the team. This situation picture includes not only an overview of the environment but also the positions, i.e., localization, of the emergency forces. The overview of the environment can be obtained either from known situation pictures like floorplans or by scanning the environment with the aid of visual sensors. The self-localization problem can be solved outdoors using the Global Navigation Satellite System (GNSS), but it is not fully solved indoors, where the GNSS signal might not be received or might be degraded. In this paper, we propose a novel combination of an inertial localization technique based on simultaneous localization and mapping (SLAM) with 3D building scans, which are used as prior information, for geo-referencing the positions, obtaining a situation picture, and finally visualizing the results with an appropriate visualization tool. We developed a new method for converting point clouds into a hexagonal prism map specifically designed for our SLAM algorithm. With this combination, we could keep the equipment for first responders as lightweight as required. We showed that the positioning led to an average accuracy of less than 1m indoors, and the final visualization including the building layout obtained by the 3D building econstruction will be advantageous for coordinating first responder operations